Trade-offs between gene expression, growth and phenotypic diversity in microbial populations

Tailored expression of ICCM cutinase in engineered Escherichia coli for efficient polyethylene terephthalate hydrolysis

Enzymatic depolymerization of PET waste emerges as a crucial and sustainable solution for combating environmental pollution. Over the past decade, PET hydrolytic enzymes, such as PETase from Ideonella sakaiensis (IsPETases), leaf compost cutinases (LCC), and lipases, have been subjected to rational mutation to enhance their enzymatic properties. ICCM, one of the best LCC mutants, was selected for overexpression in Escherichia coli BL21(DE3) for in vitro PET degradation. However, overexpressing ICCM presents challenges due to its low productivity. A new stress-inducible T7RNA polymerase-regulating E. coli strain, ASIAhsp, which significantly enhances ICCM production by 72.8 % and achieves higher enzyme solubility than other strains. The optimal cultural condition at 30 °C with high agitation, corresponding to high dissolved oxygen levels, has brought the maximum productivity of ICCM and high PET-hydrolytic activity. The most effective PET biodegradation using crude or pure ICCM occurred at pH 10 and 60 °C. Moreover, ICCM exhibited remarkable thermostability, retaining 60 % activity after a 5-day reaction at 60 °C. Notably, crude ICCM eliminates the need for purification and efficiently degrades PET films.

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions

Fast growth phenotypes are achieved through optimal transcriptomic allocation, in which cells must balance tradeoffs in resource allocation between diverse functions. One such balance between stress readiness and unbridled growth in E. coli has been termed the fear versus greed (f/g) tradeoff. Two specific RNA polymerase (RNAP) mutations observed in adaptation to fast growth have been previously shown to affect the f/g tradeoff, suggesting that genetic adaptations may be primed to control f/g resource allocation. Here, we conduct a greatly expanded study of the genetic control of the f/g tradeoff across diverse conditions. We introduced 12 RNA polymerase (RNAP) mutations commonly acquired during adaptive laboratory evolution (ALE) and obtained expression profiles of each. We found that these single RNAP mutation strains resulted in large shifts in the f/g tradeoff primarily in the RpoS regulon and ribosomal genes, likely through modifying RNAP-DNA interactions. Two of these mutations additionally caused condition-specific transcriptional adaptations. While this tradeoff was previously characterized by the RpoS regulon and ribosomal expression, we find that the GAD regulon plays an important role in stress readiness and ppGpp in translation activity, expanding the scope of the tradeoff. A phylogenetic analysis found the greed-related genes of the tradeoff present in numerous bacterial species. The results suggest that the f/g tradeoff represents a general principle of transcriptome allocation in bacteria where small genetic changes can result in large phenotypic adaptations to growth conditions.IMPORTANCETo increase growth, E. coli must raise ribosomal content at the expense of non-growth functions. Previous studies have linked RNAP mutations to this transcriptional shift and increased growth but were focused on only two mutations found in the protein's central region. RNAP mutations, however, commonly occur over a large structural range. To explore RNAP mutations' impact, we have introduced 12 RNAP mutations found in laboratory evolution experiments and obtained expression profiles of each. The mutations nearly universally increased growth rates by adjusting said tradeoff away from non-growth functions. In addition to this shift, a few caused condition-specific adaptations. We explored the prevalence of this tradeoff across phylogeny and found it to be a widespread and conserved trend among bacteria.

Phosphoribosylpyrophosphate synthetase as a metabolic valve advances Methylobacterium/Methylorubrum phyllosphere colonization and plant growth

The proficiency of phyllosphere microbiomes in efficiently utilizing plant-provided nutrients is pivotal for their successful colonization of plants. The methylotrophic capabilities of Methylobacterium/Methylorubrum play a crucial role in this process. However, the precise mechanisms facilitating efficient colonization remain elusive. In the present study, we investigate the significance of methanol assimilation in shaping the success of mutualistic relationships between methylotrophs and plants. A set of strains originating from Methylorubrum extorquens AM1 are subjected to evolutionary pressures to thrive under low methanol conditions. A mutation in the phosphoribosylpyrophosphate synthetase gene is identified, which converts it into a metabolic valve. This valve redirects limited C1-carbon resources towards the synthesis of biomass by up-regulating a non-essential phosphoketolase pathway. These newly acquired bacterial traits demonstrate superior colonization capabilities, even at low abundance, leading to increased growth of inoculated plants. This function is prevalent in Methylobacterium/Methylorubrum strains. In summary, our findings offer insights that could guide the selection of Methylobacterium/Methylorubrum strains for advantageous agricultural applications.

High variation of virulence in Aphanomyces astaci strains lacks association with pathogenic traits and mtDNA haplogroups

Introduced into Europe from North America 150 years ago alongside its native crayfish hosts, the invasive pathogen Aphanomyces astaci is considered one of the main causes of European crayfish population decline. For the past two centuries, this oomycete pathogen has been extensively studied, with the more recent efforts focused on containing and monitoring its spread across the continent. However, after the recent introduction of new strains, the newly-discovered diversity of A. astaci in North America and several years of coevolution with its European host, a new assessment of the traits linked to the pathogen's virulence is much needed. To fill this gap, we investigated the presence of phenotypic patterns (i.e., in vitro growth and sporulation rates) possibly associated with the pathogen's virulence (i.e., induced mortality in crayfish) in a collection of 14 A. astaci strains isolated both in North America and in Europe. The results highlighted a high variability in virulence, growth rate and motile spore production among the different strains, while the total-sporulation rate was more similar across strains. Surprisingly, growth and sporulation rates were not significantly correlated with virulence. Furthermore, none of the analysed parameters, including virulence, was significantly different among the major A. astaci haplogroups. These results indicate that each strain is defined by a characteristic combination of pathogenic features, specifically assembled for the environment and host faced by each strain. Thus, canonical mitochondrial markers, often used to infer the pathogen's virulence, are not accurate tools to deduce the phenotype of A. astaci strains. As the diversity of A. astaci strains in Europe is bound to increase due to translocations of new carrier crayfish species from North America, there is an urgent need to deepen our understanding of A. astaci's virulence variability and its ability to adapt to new hosts and environments.

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Saccharomyces cerevisiae has been conveniently used to produce Taxol® anticancer drug early precursors. However, the harmful impact of oxidative stress by the first cytochrome P450-reductase enzymes (CYP725A4-POR) of Taxol® pathway has hampered sufficient progress in yeast. Here, we evolved an oxidative stress-resistant yeast strain with three-fold higher titre of their substrate, taxadiene. The performance of the evolved and parent strains were then evaluated in galactose-limited chemostats before and under the oxidative stress by an oxidising agent. The interaction of evolution and oxidative stress was comprehensively evaluated through transcriptomics and metabolite profiles integration in yeast enzyme-constrained genome scale model. Overall, the evolved strain showed improved respiration, reduced overflow metabolites production and oxidative stress re-induction tolerance. The cross-protection mechanism also potentially contributed to better heme, flavin and NADPH availability, essential for CYP725A4 and POR optimal activity in yeast. The results imply that the evolved strain is a robust cell factory for future efforts towards Taxol© production.

Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Specific codons control cellular resources and fitness

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

Evaluation of the Differential Postbiotic Potential of Shewanella putrefaciens Pdp11 Cultured in Several Growing Conditions

The increased knowledge of functional foods has led to the development of a new generation of health products, including those containing probiotics and products derived from them. Shewanella putrefaciens Pdp11 (SpPdp11) is a strain described as a probiotic that exerts important beneficial effects on several farmed fish. However, the use of live probiotic cells in aquaculture has limitations such as uncertain survival and shelf life, which can limit their efficacy. In addition, its efficacy can vary across species and hosts. When probiotics are administered orally, their activity can be affected by the environment present in the host and by interactions with the intestinal microbiota. Furthermore, live cells can also produce undesired substances that may negatively impact the host as well as the risk of potential virulence reversion acquired such as antibiotic resistance. Therefore, new alternatives emerged such as postbiotics. Currently, there is no knowledge about the postbiotic potential of SpPdp11 in the aquaculture industry. Postbiotic refers to the use of bacterial metabolites, including extracellular products (ECPs), to improve host physiology. However, the production of postbiotic metabolites can be affected by various factors such as cultivation conditions, which can affect bacterial metabolism. Thus, the objective of this study was to evaluate the postbiotic potential of ECPs from SpPdp11 under different cultivation conditions, including culture media, temperature, growth phase, and salinity. We analyzed their hydrolytic, antibacterial, antiviral, and cytotoxic capacity on several fish cell lines. The results obtained have demonstrated how each ECP condition can exert a different hydrolytic profile, reduce the biofilm formation by bacterial pathogens relevant to fish, lower the titer of nervous necrosis virus (NNV), and exert a cytotoxic effect on different fish cell lines. In conclusion, the ECPs obtained from SpPdp11 have different capacities depending on the cultivation conditions used. These conditions must be considered in order to recover the maximum number of beneficial capacities or to choose the appropriate conditions for specific activities.

Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains

Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.

The distinct translational landscapes of gram-negative Salmonella and gram-positive Listeria

Translational control in pathogenic bacteria is fundamental to gene expression and affects virulence and other infection phenotypes. We used an enhanced ribosome profiling protocol coupled with parallel transcriptomics to capture accurately the global translatome of two evolutionarily distant pathogenic bacteria-the Gram-negative bacterium Salmonella and the Gram-positive bacterium Listeria. We find that the two bacteria use different mechanisms to translationally regulate protein synthesis. In Salmonella, in addition to the expected correlation between translational efficiency and cis-regulatory features such as Shine-Dalgarno (SD) strength and RNA secondary structure around the initiation codon, our data reveal an effect of the 2nd and 3rd codons, where the presence of tandem lysine codons (AAA-AAA) enhances translation in both Salmonella and E. coli. Strikingly, none of these features are seen in efficiently translated Listeria transcripts. Instead, approximately 20% of efficiently translated Listeria genes exhibit 70 S footprints seven nt upstream of the authentic start codon, suggesting that these genes may be subject to a novel translational initiation mechanism. Our results show that SD strength is not a direct hallmark of translational efficiency in all bacteria. Instead, Listeria has evolved additional mechanisms to control gene expression level that are distinct from those utilised by Salmonella and E. coli.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Genomes comparison of two Proteus mirabilis clones showing varied swarming ability

BACKGROUND

Proteus mirabilis is a Gram-negative bacteria most noted for its involvement with catheter-associated urinary tract infections. It is also known for its multicellular migration over solid surfaces, referred to as 'swarming motility'. Here we analyzed the genomic sequences of two P. mirabilis isolates, designated K38 and K39, which exhibit varied swarming ability.

METHODS AND RESULTS

The isolates genomes were sequenced using Illumina NextSeq sequencer, resulting in about 3.94 Mbp, with a GC content of 38.6%, genomes. Genomes were subjected for in silico comparative investigation. We revealed that, despite a difference in swarming motility, the isolates showed high genomic relatedness (up to 100% ANI similarity), suggesting that one of the isolates probably originated from the other.

CONCLUSIONS

The genomic sequences will allow us to investigate the mechanism driving this intriguing phenotypic heterogeneity between closely related P. mirabilis isolates. Phenotypic heterogeneity is an adaptive strategy of bacterial cells to several environmental pressures. It is also an important factor related to their pathogenesis. Therefore, the availability of these genomic sequences will facilitate studies that focus on the host-pathogen interactions during catheter-associated urinary tract infections.

Shaping bacterial gene expression by physiological and proteome allocation constraints

Networks of molecular regulators are often the primary objects of focus in the study of gene regulation, with the machinery of protein synthesis tacitly relegated to the background. Shifting focus to the constraints imposed by the allocation of protein synthesis flux reveals surprising ways in which the actions of molecular regulators are shaped by physiological demands. Using carbon catabolite repression as a case study, we describe how physiological constraints are sensed through metabolic fluxes and how flux-controlled regulation gives rise to simple empirical relations between protein levels and the rate of cell growth.

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions

Fit phenotypes are achieved through optimal transcriptomic allocation. Here, we performed a high-resolution, multi-scale study of the transcriptomic tradeoff between two key fitness phenotypes, stress response (fear) and growth (greed), in Escherichia coli. We introduced twelve RNA polymerase (RNAP) mutations commonly acquired during adaptive laboratory evolution (ALE) and found that single mutations resulted in large shifts in the fear vs. greed tradeoff, likely through destabilizing the rpoB-rpoC interface. RpoS and GAD regulons drive the fear response while ribosomal proteins and the ppGpp regulon underlie greed. Growth rate selection pressure during ALE results in endpoint strains that often have RNAP mutations, with synergistic mutations reflective of particular conditions. A phylogenetic analysis found the tradeoff in numerous bacteria species. The results suggest that the fear vs. greed tradeoff represents a general principle of transcriptome allocation in bacteria where small genetic changes can result in large phenotypic adaptations to growth conditions.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

Hardware, Software, and Wetware Codesign Environment for Synthetic Biology

Synthetic biology is the process of forward engineering living systems. These systems can be used to produce biobased materials, agriculture, medicine, and energy. One approach to designing these systems is to employ techniques from the design of embedded electronics. These techniques include abstraction, standards, modularity, automated design, and formal semantic models of computation. Together, these elements form the foundation of "biodesign automation," where software, robotics, and microfluidic devices combine to create exciting biological systems of the future. This paper describes a "hardware, software, wetware" codesign vision where software tools can be made to act as "genetic compilers" that transform high-level specifications into engineered "genetic circuits" (wetware). This is followed by a process where automation equipment, well-defined experimental workflows, and microfluidic devices are explicitly designed to house, execute, and test these circuits (hardware). These systems can be used as either massively parallel experimental platforms or distributed bioremediation and biosensing devices. Next, scheduling and control algorithms (software) manage these systems' actual execution and data analysis tasks. A distinguishing feature of this approach is how all three of these aspects (hardware, software, and wetware) may be derived from the same basic specification in parallel and generated to fulfill specific cost, performance, and structural requirements.

The context matrix: Navigating biological complexity for advanced biodesign

Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.

Process Intensification at the expression system level for the production of 1-phosphate aldolase in antibiotic-free E. coli fed-batch cultures

To successfully design expression systems for industrial biotechnology and biopharmaceutical applications; plasmid stability, efficient synthesis of the desired product and the use of selection markers acceptable to regulatory bodies are of utmost importance. In this work we demonstrate the application of a set of IPTG-inducible protein expression systems -- harboring different features namely, antibiotic vs auxotrophy marker; two-plasmids vs single plasmid expression system; expression levels of the repressor protein (LacI) and the auxotrophic marker (glyA) -- in high-cell density cultures to evaluate their suitability in bioprocess conditions that resemble industrial settings. Results revealed that the first generation of engineered strain showed a 50% reduction in the production of the model recombinant protein fuculose-1-phosphate aldolase (FucA) compared to the reference system from QIAGEN. The over-transcription of glyA was found to be a major factor responsible for the metabolic burden. The second- and third-generation of expression systems presented an increase in FucA production and advantageous features. In particular, the third-generation expression system is antibiotic-free, autotrophy-selection based and single-plasmid and, is capable to produce FucA at similar levels compared to the original commercial expression system. These new tools open new avenues for high-yield and robust expression of recombinant proteins in E. coli.

Adaptation of the gut pathobiont Enterococcus faecalis to deoxycholate and taurocholate bile acids

Enterococcus faecalis is a natural inhabitant of the human gastrointestinal tract. This bacterial species is subdominant in a healthy physiological state of the gut microbiota (eubiosis) in adults, but can become dominant and cause infections when the intestinal homeostasis is disrupted (dysbiosis). The relatively high concentrations of bile acids deoxycholate (DCA) and taurocholate (TCA) hallmark eubiosis and dysbiosis, respectively. This study aimed to better understand how E. faecalis adapts to DCA and TCA. We showed that DCA impairs E. faecalis growth and possibly imposes a continuous adjustment in the expression of many essential genes, including a majority of ribosomal proteins. This may account for slow growth and low levels of E. faecalis in the gut. In contrast, TCA had no detectable growth effect. The evolving transcriptome upon TCA adaptation showed the early activation of an oligopeptide permease system (opp2) followed by the adjustment of amino acid and nucleotide metabolisms. We provide evidence that TCA favors the exploitation of oligopeptide resources to fuel amino acid needs in limiting oligopeptide conditions. Altogether, our data suggest that the combined effects of decreased DCA and increased TCA concentrations can contribute to the rise of E. faecalis population during dysbiosis.

Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug's action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli

Objective

MazF is a sequence-specific endoribonuclease-toxin of the MazEF toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli. The MazEF system has been used in various biotechnology and synthetic biology applications. In this study, we infer how ectopic mazF overexpression affects production of heterologous proteins. To this end, we quantified the levels of fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the 5′-untranslated region of these reporter mRNAs under the same conditions by comparing expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless mRNA).

Results

Flow cytometry analysis indicates that during mazF overexpression, fluorescent proteins are translated from the canonical as well as leaderless mRNAs. Our analysis further indicates that longer mazF overexpression generally increases the concentration of fluorescent proteins translated from ACA-less mRNAs, however it also substantially increases bacterial population heterogeneity. Finally, our results suggest that the strength and duration of mazF overexpression should be optimized for each experimental setup, to maximize the heterologous protein production and minimize the amount of phenotypic heterogeneity in bacterial populations, which is unfavorable in biotechnological processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-06061-9.

Regulatory perturbations of ribosome allocation in bacteria reshape the growth proteome with a trade-off in adaptation capacity

Bacteria regulate their cellular resource allocation to enable fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth, and expression profiles of two sets of fast-growing mutants of Escherichia coli K-12 MG1655. Mutants with only three of the seven copies of ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied fast-growing rpoB mutants. Comparing these two different regulatory perturbations (rRNA promoters or rpoB mutations), we show how they reshape the proteome for growth with a concomitant fitness cost. The fast-growing mutants shared downregulation of hedging functions and upregulated growth functions. They showed longer diauxic shifts and reduced activity of gluconeogenic promoters during glucose-acetate shifts, suggesting reduced availability of the RNA polymerase for expressing hedging proteome. These results show that the regulation of ribosomal allocation underlies the growth/hedging phenotypes obtained from laboratory evolution experiments.

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Mutants with only three ribosomal operons grow faster than wild-type in minimal medium

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Faster growth of mutants is achieved by increased ribosome content

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Fast-growing mutants display reduced hedging expression and adaptation trade-offs

Predictive Potential of MALDI-TOF Analyses for Wine and Brewing Yeast

The potential of MALDI-TOF profiling for predicting potential applications of yeast strains in the beverage sector was assessed. A panel of 59 commercial yeasts (47 wine and 12 brewing yeasts) was used to validate the concept whereby 2 culture media (YPD agar and YPD broth), as well as two mass ranges m/z 500–4000 and m/z 2000–20,000, were evaluated for the best fit. Three machine learning-based algorithms, PCA, MDS, and UMAP, in addition to a hierarchical clustering method, were employed. Profiles derived from broth cultures yielded more peaks, but these were less well-defined compared with those from agar cultures. Hierarchical clustering more clearly resolved different species and gave a broad overview of potential strain utility, but more nuanced insights were provided by MDS and UMAP analyses. PCA-based displays were less informative. The potential of MALDI-TOF proteomics in predicting the utility of yeast strains of commercial benefit is supported in this study, provided appropriate approaches are used for data generation and analysis.

Microbial adaptation to different environmental conditions: molecular perspective of evolved genetic and cellular systems

Microorganisms are ubiquitous on Earth and can inhabit almost every environment. In a complex heterogeneous environment or in face of ecological disturbance, the microbes adjust to fluctuating environmental conditions through a cascade of cellular and molecular systems. Their habitats differ from cold microcosms of Antarctica to the geothermal volcanic areas, terrestrial to marine, highly alkaline zones to the extremely acidic areas and freshwater to brackish water sources. The diverse ecological microbial niches are attributed to the versatile, adaptable nature under fluctuating temperature, nutrient availability and pH of the microorganisms. These organisms have developed a series of mechanisms to face the environmental changes and thereby keep their role in mediate important ecosystem functions. The underlying mechanisms of adaptable microbial nature are thoroughly investigated at the cellular, genetic and molecular levels. The adaptation is mediated by a spectrum of processes like natural selection, genetic recombination, horizontal gene transfer, DNA damage repair and pleiotropy-like events. This review paper provides the fundamentals insight into the microbial adaptability besides highlighting the molecular network of microbial adaptation under different environmental conditions.

Analysis of the transcriptome of the needles and bark of Pinus radiata induced by bark stripping and methyl jasmonate

BACKGROUND

Plants are attacked by diverse insect and mammalian herbivores and respond with different physical and chemical defences. Transcriptional changes underlie these phenotypic changes. Simulated herbivory has been used to study the transcriptional and other early regulation events of these plant responses. In this study, constitutive and induced transcriptional responses to artificial bark stripping are compared in the needles and the bark of Pinus radiata to the responses from application of the plant stressor, methyl jasmonate. The time progression of the responses was assessed over a 4-week period.

RESULTS

Of the 6312 unique transcripts studied, 86.6% were differentially expressed between the needles and the bark prior to treatment. The most abundant constitutive transcripts were related to defence and photosynthesis and their expression did not differ between the needles and the bark. While no differential expression of transcripts were detected in the needles following bark stripping, in the bark this treatment caused an up-regulation and down-regulation of genes associated with primary and secondary metabolism. Methyl jasmonate treatment caused differential expression of transcripts in both the bark and the needles, with individual genes related to primary metabolism more responsive than those associated with secondary metabolism. The up-regulation of genes related to sugar break-down and the repression of genes related with photosynthesis, following both treatments was consistent with the strong down-regulation of sugars that has been observed in the same population. Relative to the control, the treatments caused a differential expression of genes involved in signalling, photosynthesis, carbohydrate and lipid metabolism as well as defence and water stress. However, non-overlapping transcripts were detected between the needles and the bark, between treatments and at different times of assessment. Methyl jasmonate induced more transcriptional responses in the bark than bark stripping, although the peak of expression following both treatments was detected 7 days post treatment application. The effects of bark stripping were localised, and no systemic changes were detected in the needles.

CONCLUSION

There are constitutive and induced differences in the needle and bark transcriptome of Pinus radiata. Some expression responses to bark stripping may differ from other biotic and abiotic stresses, which contributes to the understanding of plant molecular responses to diverse stresses. Whether the gene expression changes are heritable and how they differ between resistant and susceptible families identified in earlier studies needs further investigation.

Advances and prospects in metabolic engineering of Escherichia coli for L-tryptophan production

As an important raw material for pharmaceutical, food and feed industry, highly efficient production of L-tryptophan by Escherichia coli has attracted a considerable attention. However, there are complicated and multiple layers of regulation networks in L-tryptophan biosynthetic pathway and thus have difficulty to rewrite the biosynthetic pathway for producing L-tryptophan with high efficiency in E. coli. This review summarizes the biosynthetic pathway of L-tryptophan and highlights the main regulatory mechanisms in E. coli. In addition, we discussed the latest metabolic engineering strategies achieved in E. coli to reconstruct the L-tryptophan biosynthetic pathway. Moreover, we also review a few strategies that can be used in E. coli to improve robustness and streamline of L-tryptophan high-producing strains. Lastly, we also propose the potential strategies to further increase L-tryptophan production by systematic metabolic engineering and synthetic biology techniques.

Protein concentration fluctuations in the high expression regime: Taylor's law and its mechanistic origin

Protein concentration in a living cell fluctuates over time due to noise in growth and division processes. In the high expression regime, variance of the protein concentration in a cell was found to scale with the square of the mean, which belongs to a general phenomenon called Taylor's law (TL). To understand the origin for these fluctuations, we measured protein concentration dynamics in single E. coli cells from a set of strains with a variable expression of fluorescent proteins. The protein expression is controlled by a set of constitutive promoters with different strength, which allows to change the expression level over 2 orders of magnitude without introducing noise from fluctuations in transcription regulators. Our data confirms the square TL, but the prefactor A has a cell-to-cell variation independent of the promoter strength. Distributions of the normalized protein concentration for different promoters are found to collapse onto the same curve. To explain these observations, we used a minimal mechanistic model to describe the stochastic growth and division processes in a single cell with a feedback mechanism for regulating cell division. In the high expression regime where extrinsic noise dominates, the model reproduces our experimental results quantitatively. By using a mean-field approximation in the minimal model, we showed that the stochastic dynamics of protein concentration is described by a Langevin equation with multiplicative noise. The Langevin equation has a scale invariance which is responsible for the square TL. By solving the Langevin equation, we obtained an analytical solution for the protein concentration distribution function that agrees with experiments. The solution shows explicitly how the prefactor A depends on strength of different noise sources, which explains its cell-to-cell variability. By using this approach to analyze our single-cell data, we found that the noise in production rate dominates the noise from cell division. The deviation from the square TL in the low expression regime can also be captured in our model by including intrinsic noise in the production rate.

Continuous H2/CO2 fermentation for acetic acid production under transient and continuous sulfide inhibition

Waste gas fermentation powered by renewable H₂ is reaching kiloton scale. The presence of sulfide, inherent to many waste gases, can cause inhibition, requiring additional gas treatment. In this work, acetogenesis and methanogenesis inhibition by sulfide were studied in a 10-L mixed-culture fermenter, supplied with CO₂ and connected with a water electrolysis unit for electricity-powered H₂ supply. Three cycles of inhibition (1.3 mM total dissolved sulfide (TDS)) and recovery were applied, then the fermenter was operated at 0.5 mM TDS for 35 days. During operation at 0.5 mM TDS the acetate production rate reached 7.1 ± 1.5 mmol C L^-1 d^-1. Furthermore, 43.7 ± 15.6% of the electrons, provided as H₂, were distributed to acetate and 7.7 ± 4.1% to butyrate, the second most abundant fermentation product. Selectivity of sulfide as inhibitor was demonstrated by a 7 days lag-phase of methanogenesis recovery, compared to 48 h for acetogenesis and by the less than 1% electrons distribution to CH₄, under 0.5 mM TDS. The microbial community was dominated by Eubacterium, Proteiniphilum and an unclassified member of the Eggerthellaceae family. The taxonomic diversity of the community decreased and conversely the phenotypic diversity increased, during operation. This work illustrated the scale-up potential of waste gas fermentations, by elucidating the effect of sulfide as a common gas impurity, and by demonstrating continuous, potentially renewable supply of electrons.

Emergent correlations in gene expression dynamics as footprints of resource competition

Genetic circuits need a cellular environment to operate in, which naturally couples the circuit function with the overall functionality of gene regulatory network. To execute their functions, all gene circuits draw resources in the form of RNA polymerases, ribosomes, and tRNAs. Recent experiments pointed out that the role of resource competition on synthetic circuit outputs could be immense. However, the effect of complexity of the circuit architecture on resource sharing dynamics is yet unexplored. In this paper, we employ mathematical modelling and in-silico experiments to identify the sources of resource trade-off and to quantify its impact on the function of a genetic circuit, keeping our focus on regulation of immediate downstream proteins, which are often used as protein read-outs. We show that estimating gene expression dynamics from readings of downstream protein data might be unreliable when the resource is limited and ribosome affinities are asymmetric. We focus on the impact of mRNA copy number and ribosome binding site (RBS) strength on the nonlinear isocline that emerges with two regimes, prominently separated by a tipping point, and study how correlation and competition dominate each other depending on various circuit parameters. Focusing further on genetic toggle circuit, we have identified major effects of resource competition in this model motif and quantified the observations. The observations are testable in wet-lab experiments, as all the parameters chosen are experimentally relevant.

Regulating the T7 RNA polymerase expression in E. coli BL21 (DE3) to provide more host options for recombinant protein production

Escherichia coli is the most widely used bacterium in prokaryotic expression system for the production of recombinant proteins. In BL21 (DE3), the gene encoding the T7 RNA polymerase (T7 RNAP) is under control of the strong lacUV5 promoter (P_lacUV5), which is leakier and more active than wild-type lac promoter (P_lacWT) under certain growth conditions. These characteristics are not advantageous for the production of those recombinant proteins with toxic or growth-burdened. On the one hand, leakage expression of T7 RNAP leads to rapid production of target proteins under non-inducing period, which sucks resources away from cellular growth. Moreover, in non-inducing or inducing period, high expression of T7 RNAP production leads to the high-production of hard-to-express proteins, which may all lead to loss of the expression plasmid or the occurrence of mutations in the expressed gene. Therefore, more BL21 (DE3)-derived variant strains with rigorous expression and different expression level of T7 RNAP should be developed. Hence, we replaced P_lacUV5 with other inducible promoters respectively, including arabinose promoter (P_araBAD), rhamnose promoter (P_rhaBAD), tetracycline promoter (P_tet), in order to optimize the production of recombinant protein by regulating the transcription level and the leakage level of T7 RNAP. Compared with BL21 (DE3), the constructed engineered strains had higher sensitivity to inducers, among which rhamnose and tetracycline promoters had the lowest leakage ability. In the production of glucose dehydrogenase (GDH), a protein that causes host autolysis, the engineered strain BL21 (DE3::ara) exhibited higher biomass, cell survival rate and foreign protein expression level than that of BL21 (DE3). In addition, these engineered strains had been successfully applied to improve the production of membrane proteins, including E. coli cytosine transporter protein (CodB), the E. coli membrane protein insertase/foldase (YidC), and the E. coli F-ATPase subunit b (Ecb). The engineered strains constructed in this paper provided more host choices for the production of recombinant proteins.

Flow cytometric monitoring of the bacterial phenotypic diversity in aquatic ecosystems

Flow cytometry is a promising tool used to identify the phenotypic features of bacterial communities in aquatic ecosystems by measuring the physical and chemical properties of cells based on their light scattering behavior and fluorescence. Compared to molecular or culture-based approaches, flow cytometry is suitable for the online monitoring of microbial water quality because of its relatively simple sample preparation process, rapid analysis time, and high-resolution phenotypic data. Advanced statistical techniques (e.g., denoising and binning) can be utilized to successfully calculate phenotypic diversity by processing the scatter data obtained from flow cytometry. These phenotypic diversities were well correlated with taxonomic-based diversity computed using next-generation 16S RNA gene sequencing. The protocol provided in this paper should be a useful guide for a fast and reliable flow cytometric monitoring of bacterial phenotypic diversity in aquatic ecosystems.

An Unnatural Amino Acid-Regulated Growth Controller Based on Informational Disturbance

We designed a novel growth controller regulated by feeding of an unnatural amino acid, N^ε-benzyloxycarbonyl-l-lysine (ZK), using a specific incorporation system at a sense codon. This system is constructed by a pair of modified pyrrolisyl-tRNA synthetase (PylRS) and its cognate tRNA (tRNA^pyl). Although ZK is non-toxic for normal organisms, the growth of Escherichia coli carrying the ZK incorporation system was inhibited in a ZK concentration-dependent manner without causing rapid bacterial death, presumably due to generation of non-functional or toxic proteins. The extent of growth inhibition strongly depended on the anticodon sequence of the tRNA^pyl gene. Taking advantage of the low selectivity of PylRS for tRNA^pyl anticodons, we experimentally determined the most effective anticodon sequence among all 64 nucleotide sequences in the anticodon region of tRNA^pyl gene. The results suggest that the ZK-regulated growth controller is a simple, target-specific, environmental noise-resistant and titratable system. This technique may be applicable to a wide variety of organisms because the growth inhibitory effects are caused by "informational disturbance", in which the highly conserved system for transmission of information from DNA to proteins is perturbed.

A novel global transcriptional perturbation target identified by forward genetics reprograms Vibrio natriegens for improving recombinant protein production

Vibrio natriegens is known to be the fastest-growing free-living bacterium with the potential to be a novel protein expression system other than Escherichia coli. Seven sampled genes of interest (GOIs) encoding biocatalyst enzymes, including Ochrobactrum anthropi-derived ω-transaminase (OATA), were strongly expressed in E. coli but weakly in V. natriegens using the pET expression system. In this study, we fused the C-terminal of OATA with green fluorescent protein (GFP) and obtained V. natriegens mutants that could increase both protein yield and enzyme activity of OATA as well as the other three GOIs by ultraviolet mutagenesis, fluorescence-activated cell sorting (FACS), and OATA colorimetric assay. Furthermore, next-generation sequencing and strain reconstruction revealed that the Y457 variants in the conserved site of endogenous RNA polymerase (RNAP) β' subunit rpoC are responsible for the increase in recombinant protein yield. We speculated that the mutation of rpoC Y457 may reprogram V. natriegens's innate gene transcription, thereby increasing the copy number of pET plasmids and soluble protein yield of certain GOIs. The increase in GOI expression may partly be attributed to the increase in copy number. In conclusion, GOI-GFP fusion combined with FACS is a powerful tool of forward genetics that can be used to obtain a superior expression chassis. If more high-expression-related targets are found for more GOIs, it would make the construction of next-generation protein expression chassis more time-saving.

Picking the right metaphors for addressing microbial systems: economic theory helps understanding biological complexity

Any descriptive language is necessarily metaphoric and interpretative. Two somewhat overlapping-but not identical-languages have been thoroughly employed in the last decade to address the issue of regulatory complexity in biological systems: the terminology of network theory and the jargon of electric circuitry. These approaches have found many formal equivalences between the layout of extant genetic circuits and the architecture of man-made counterparts. However, these languages still fail to describe accurately key features of biological objects, in particular the diversity of signal-transfer molecules and the diffusion that is inherent to any biochemical system. Furthermore, current formalisms associated with networks and circuits can hardly face the problem of multi-scale regulatory complexity-from single molecules to entire ecosystems. We argue that the language of economic theory might be instrumental not only to portray accurately many features of regulatory networks, but also to unveil aspects of the biological complexity problem that remain opaque to other types of analyses. The main perspective opened by the economic metaphor when applied to control of microbiological activities is a focus on metabolism, not gene selfishness, as the necessary background to make sense of regulatory phenomena. As an example, we analyse and reinterpret the widespread phenomenon of catabolite repression with the formal frame of the consumer's choice theory.

Charting the landscape of RNA polymerases to unleash their potential in strain improvement

One major mission of microbial cell factory is overproduction of desired chemicals. To this end, it is necessary to orchestrate enzymes that affect metabolic fluxes. However, only modification of a small number of enzymes in most cases cannot maximize desired metabolites, and global regulation is required. Of myriad enzymes influencing global regulation, RNA polymerase (RNAP) may be the most versatile enzyme in biological realm because it not only serves as the workhorse of central dogma but also participates in a plethora of biochemical events. In fact, recent years have witnessed extensive exploitation of RNAPs for phenotypic engineering. While a few impressive reviews showcase the structures and functionalities of RNAPs, this review not only summarizes the state-of-the-art advance in the structures of RNAPs but also points out their enormous potentials in metabolic engineering and synthetic biology. This review aims to provide valuable insights for strain improvement.

Multiscale Assay of Unlabeled Neurite Dynamics Using Phase Imaging with Computational Specificity

Primary neuronal cultures have been widely used to study neuronal morphology, neurophysiology, neurodegenerative processes, and molecular mechanism of synaptic plasticity underlying learning and memory. However, the unique behavioral properties of neurons make them challenging to study, with phenotypic differences expressed as subtle changes in neuronal arborization rather than easy-to-assay features such as cell count. The need to analyze morphology, growth, and intracellular transport has motivated the development of increasingly sophisticated microscopes and image analysis techniques. Due to its high-contrast, high-specificity output, many assays rely on confocal fluorescence microscopy, genetic methods, or antibody staining techniques. These approaches often limit the ability to measure quantitatively dynamic activity such as intracellular transport and growth. In this work, we describe a method for label-free live-cell cell imaging with antibody staining specificity by estimating the associated fluorescence signals via quantitative phase imaging and deep convolutional neural networks. This computationally inferred fluorescence image is then used to generate a semantic segmentation map, annotating subcellular compartments of live unlabeled neural cultures. These synthetic fluorescence maps were further applied to study the time-lapse development of hippocampal neurons, highlighting the relationships between the cellular dry mass production and the dynamic transport activity within the nucleus and neurites. Our implementation provides a high-throughput strategy to analyze neural network arborization dynamically, with high specificity and without the typical phototoxicity and photobleaching limitations associated with fluorescent markers.

Cerebrospinal fluid (CSF) augments metabolism and virulence expression factors in Acinetobacter baumannii

In a recent report by the Centers for Disease Control and Prevention (CDC), multidrug resistant (MDR) Acinetobacter baumannii is a pathogen described as an "urgent threat." Infection with this bacterium manifests as different diseases such as community and nosocomial pneumonia, bloodstream infections, endocarditis, infections of the urinary tract, wound infections, burn infections, skin and soft tissue infections, and meningitis. In particular, nosocomial meningitis, an unwelcome complication of neurosurgery caused by extensively-drug resistant (XDR) A. baumannii, is extremely challenging to manage. Therefore, understanding how A. baumannii adapts to different host environments, such as cerebrospinal fluid (CSF) that may trigger changes in expression of virulence factors that are associated with the successful establishment and progress of this infection is necessary. The present in-vitro work describes, the genetic changes that occur during A. baumannii infiltration into CSF and displays A. baumannii's expansive versatility to persist in a nutrient limited environment while enhancing several virulence factors to survive and persist. While a hypervirulent A. baumannii strain did not show changes in its transcriptome when incubated in the presence of CSF, a low-virulence isolate showed significant differences in gene expression and phenotypic traits. Exposure to 4% CSF caused increased expression of virulence factors such as fimbriae, pilins, and iron chelators, and other virulence determinants that was confirmed in various model systems. Furthermore, although CSF's presence did not enhance bacterial growth, an increase of expression of genes encoding transcription, translation, and the ATP synthesis machinery was observed. This work also explores A. baumannii's response to an essential component, human serum albumin (HSA), within CSF to trigger the differential expression of genes associated with its pathoadaptibility in this environment.

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

Plant invasion impacts on fungal community structure and function depend on soil warming and nitrogen enrichment

The impacts of invasive species on biodiversity may be mitigated or exacerbated by abiotic environmental changes. Invasive plants can restructure soil fungal communities with important implications for native biodiversity and nutrient cycling, yet fungal responses to invasion may depend on numerous anthropogenic stressors. In this study, we experimentally invaded a long-term soil warming and simulated nitrogen deposition experiment with the widespread invasive plant Alliaria petiolata (garlic mustard) and tested the responses of soil fungal communities to invasion, abiotic factors, and their interaction. We focused on the phytotoxic garlic mustard because it suppresses native mycorrhizae across forests of North America. We found that invasion in combination with warming, but not under ambient conditions or elevated nitrogen, significantly reduced soil fungal biomass and ectomycorrhizal relative abundances and increased relative abundances of general soil saprotrophs and fungal genes encoding for hydrolytic enzymes. These results suggest that warming potentially exacerbates fungal responses to plant invasion. Soils collected from uninvaded and invaded plots across eight forests spanning a 4 °C temperature gradient further demonstrated that the magnitude of fungal responses to invasion was positively correlated with mean annual temperature. Our study is one of the first empirical tests to show that the impacts of invasion on fungal communities depends on additional anthropogenic pressures and were greater in concert with warming than under elevated nitrogen or ambient conditions.

Developing a population-state decision system for intelligently reprogramming extracellular electron transfer in Shewanella oneidensis

The unique extracellular electron transfer (EET) ability has positioned electroactive bacteria (EAB) as a major class of cellular chassis for genetic engineering aimed at favorable environmental, energy, and geoscience applications. However, previous efforts to genetically enhance EET ability have often impaired the basal metabolism and cellular growth due to the competition for the limited cellular resource. Here, we design a quorum sensing-based population-state decision (PSD) system for intelligently reprogramming the EET regulation system, which allows the rebalanced allocation of the cellular resource upon the bacterial growth state. We demonstrate that the electron output from Shewanella oneidensis MR-1 could be greatly enhanced by the PSD system via shifting the dominant metabolic flux from initial bacterial growth to subsequent EET enhancement (i.e., after reaching a certain population-state threshold). The strain engineered with this system achieved up to 4.8-fold EET enhancement and exhibited a substantially improved pollutant reduction ability, increasing the reduction efficiencies of methyl orange and hexavalent chromium by 18.8- and 5.5-fold, respectively. Moreover, the PSD system outcompeted the constant expression system in managing EET enhancement, resulting in considerably enhanced electron output and pollutant bioreduction capability. The PSD system provides a powerful tool for intelligently managing extracellular electron transfer and may inspire the development of new-generation smart bioelectrical devices for various applications.

Insights Into Subspecies Discrimination Potentiality From Bacteria MALDI-TOF Mass Spectra by Using Data Mining and Diversity Studies

Bacterial identification at subspecies level is critical in clinical care and epidemiological investigations due to the different epidemic potentialities of a species. For this purpose, matrix-assisted laser desorption ionization – time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed in place of molecular genotyping, but with some result discrepancies. The aim of this work is to methodically mine the expression diversities of MALDI-TOF bacterial species spectra and their possible latent organization in order to evaluate their subspecies specific expression. Peak expression diversities of MALDI-TOF spectra coming from routine identifications have been analyzed using Hill numbers, rarefaction curves, and peak clustering. Some size effect critical thresholds were estimated using change point analyses. We included 167,528 spectra corresponding to 405 species. Species spectra diversities have a broad size-dependent variability, which may be influenced by the kind of sampling. Peak organization is characterized by the presence of a main cluster made of the most frequently co-occurring peaks and around 20 secondary clusters grouping less frequently co-occurring peaks. The 35 most represented species in our sample are distributed in two groups depending on the focusing of their protein synthesis activity on the main cluster or not. Our results may advocate some analogy with genomics studies of bacteria, with a main species-related cluster of co-occurring peaks and several secondary clusters, which may host peaks able to discriminate bacterial subgroups. This systematic study of the expression diversities of MALDI-TOF spectra shows that latent organization of co-occurring peaks supports subspecies discrimination and may explain why studies on MALDI-TOF-based typing exhibit some result divergences.

A quantitative method for proteome reallocation using minimal regulatory interventions

Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.